Individualised human phenotype ontology gene panels improve clinical whole exome and genome sequencing analytical efficacy in a cohort of developmental and epileptic encephalopathies.

BACKGROUND: The majority of genetic epilepsies remain unsolved in terms of specific genotype. Phenotype-based genomic analyses have shown potential to strengthen genomic analysis in various ways, including improving analytical efficacy. METHODS: We have tested a standardised phenotyping method termed 'Phenomodels' for integrating deep-phenotyping information with our in-house developed clinical whole exome/genome sequencing analytical pipeline. Phenomodels includes a user-friendly epilepsy phenotyping template and an objective measure for selecting which template terms to include in individualised Human Phenotype Ontology (HPO) gene panels. In a pilot study of 38 previously solved cases of developmental and epileptic encephalopathies, we compared the sensitivity and specificity of the individualised HPO gene panels with the clinical epilepsy gene panel. RESULTS: The Phenomodels template showed high sensitivity for capturing relevant phenotypic information, where 37/38 individuals' HPO gene panels included the causative gene. The HPO gene panels also had far fewer variants to assess than the epilepsy gene panel. CONCLUSION: We have demonstrated a viable approach for incorporating standardised phenotype information into clinical genomic analyses, which may enable more efficient analysis.

The utility of peanut components in the diagnosis of IgE-mediated peanut allergy among distinct populations.

BACKGROUND: Increasing data suggest that analysis of IgE to peanut components can be clinically helpful and possibly more accurate than IgE to whole peanut. Not all studies examining this topic, however, have used prospective samples, multiple components, and peanut challenges. OBJECTIVE: We sought to determine the utility of peanut component testing, using a standardized, commercially available test done before oral peanut challenge in various populations of patients with suspected peanut allergy from 2 different countries. METHODS: IgE to whole peanut and the recombinant allergen components Ara h 1, 2, 3, and 8 were analyzed from serum samples drawn before double-blind peanut challenge from 4 distinct cohorts of patients with suspected peanut allergy from 2 nations (United States and Sweden). RESULTS: Patients (n = 167; median age, 11.7 years; interquartile range, 7.0-15.0 years) had serum analyzed for peanut components and completed an oral food challenge to peanut. Although IgE to peanut was the most sensitive test (0.93), Ara h 2 was the most specific (0.92) and provided the best positive predictive value (0.94) of all the tests. Ara h 2 was also the best overall diagnostic test by receiver operating characteristic analysis (area under the curve, 0.84; P < .05). CONCLUSIONS: In patients with suspected peanut allergy, IgE to peanut is a sensitive test but is not specific. IgE to Ara h 2 is a more specific and more accurate diagnostic test in this sampling of patients with suspected peanut allergy. Given each tests attributes, a stepwise approach to testing may provide clinicians with a way to minimize the need for peanut challenges.